MACHINE-LEARNING BASED ARTIFICIAL INTELLIGENCE CAPABILITY

Techniques for providing machine-learned (ML)-based artificial intelligence (AI) capabilities are described. In one technique, multiple AI capabilities are stored in a cloud environment. While the AI capabilities are stored, a request for a particular AI capability is received from a computing devic...

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Bibliographische Detailangaben
Hauptverfasser:	Akshat, FNU, Zhang, Ye, Yalamanchi, Uday Bhaskar, Varia, Pranav, Balasubramanian, Hariharan, Guo, Beiwen, Banerjee, Aditya, Mody, Jigar, Patlola, Athinder, Rajaram, Denesh Krishnan, Jagarlapudi, Abhiram, Ziklik, Elad, Vinayakumar, Shreyas, Ballingam, Varaprasad, Shah, Varun Ketanbhai, Rahmat, Safia, Ramanathan, Prashanth, Ponnappan, Senthilkumar
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING PHYSICS
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Beschreibung
Zusammenfassung:	Techniques for providing machine-learned (ML)-based artificial intelligence (AI) capabilities are described. In one technique, multiple AI capabilities are stored in a cloud environment. While the AI capabilities are stored, a request for a particular AI capability is received from a computing device of a user. Also, in response to receiving training data based on input from the user, the training data is stored in a tenancy, associated with the user, in the cloud environment. In response to receiving the request, the particular AI capability is accessed, a ML model is trained based on the particular AI capability and the training data to produce a trained ML model, and an endpoint, in the cloud environment, is generated that is associated with the trained ML model. The endpoint is provided to the tenancy associated with the user.